Given the plethora of content available for consumption, it is not always possible for users to consume a piece of content right when it is made available. In such cases, a user may record content for later consumption. However, recording devices have finite storage capacity and recorded content have to be periodically deleted from recording devices to ensure that there is storage capacity available for recording new content. Because a recording device may contain a large amount of recorded content, it is very cumbersome for a user to manually determine which recorded content should be deleted. Current systems may recommend recorded content for deletion based on a variety of factors (e.g., genre of a recording, number of playbacks, duration for which recorded content was stored on the recording device). However, current systems do not use a variety of independent rules for moving recorded content bi-directionally between multiple deletion recommendation categories. Consequently, current systems are limited to providing coarse granularity deletion recommendations that are not updated based on new information.